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  Neural network approximated Bayesian inference of edge electron density profiles at JET

Pavone, A., Svensson, J., Kwak, S., Brix, M., Wolf, R. C., & JET Contributors (2020). Neural network approximated Bayesian inference of edge electron density profiles at JET. Plasma Physics and Controlled Fusion, 62: 045019. doi:10.1088/1361-6587/ab7732.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0005-EFA5-4 Version Permalink: https://hdl.handle.net/21.11116/0000-000C-E8BE-9
Genre: Journal Article

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pavone_neural.pdf (Supplementary material), 826KB
 
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https://doi.org/10.1088/1361-6587/ab7732 (Publisher version)
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 Creators:
Pavone, A.1, Author           
Svensson, J.2, Author           
Kwak, S.2, Author           
Brix, M.3, Author
Wolf, R. C.1, Author           
JET Contributors, Author              
Affiliations:
1Stellarator Heating and Optimisation (E3), Max Planck Institute for Plasma Physics, Max Planck Society, ou_2040305              
2Stellarator Dynamics and Transport (E5), Max Planck Institute for Plasma Physics, Max Planck Society, ou_2040306              
3External Organizations, ou_persistent22              

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Language(s): eng - English
 Dates: 20192020
 Publication Status: Issued
 Pages: 13 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1088/1361-6587/ab7732
 Degree: -

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Project name : Euratom Research and Training Programme 2014-2018 and 2019-2020 – EUROfusion
Grant ID : 633053
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

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Title: Plasma Physics and Controlled Fusion
Source Genre: Journal
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Publ. Info: Bristol : IOP Publishing
Pages: - Volume / Issue: 62 Sequence Number: 045019 Start / End Page: - Identifier: ISSN: 1361-6587
CoNE: https://pure.mpg.de/cone/journals/resource/954925539167